Risk estimation using probability machines

BACKGROUND: Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. RESULTS: We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. CONCLUSIONS: The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from

Minimum Decision Cost for Quantum Ensembles

For a given ensemble of $N$ independent and identically prepared particles, we calculate the binary decision costs of different strategies for measurement of polarised spin 1/2 particles. The result proves that, for any given values of the prior probabilities and any number of constituent particles, the cost for a combined measurement is always less than or equal to that for any combination of separate measurements upon sub-ensembles. The Bayes cost, which is that associated with the optimal strategy (i.e., a combined measurement) is obtained in a simple closed form.Comment: 11 pages, uses RevTe

Performance of random forests and logic regression methods using mini-exome sequence data

Machine learning approaches are an attractive option for analyzing large-scale data to detect genetic variants that contribute to variation of a quantitative trait, without requiring specific distributional assumptions. We evaluate two machine learning methods, random forests and logic regression, and compare them to standard simple univariate linear regression, using the Genetic Analysis Workshop 17 mini-exome data. We also apply these methods after collapsing multiple rare variants within genes and within gene pathways. Linear regression and the random forest method performed better when rare variants were collapsed based on genes or gene pathways than when each variant was analyzed separately. Logic regression performed better when rare variants were collapsed based on genes rather than on pathways

Inferring Properties of Ancient Cyanobacteria from Biogeochemical Activity and Genomes of Siderophilic Cyanobacteria

Interrelationships between life and the planetary system could have simultaneously left landmarks in genomes of microbes and physicochemical signatures in the lithosphere. Verifying the links between genomic features in living organisms and the mineralized signatures generated by these organisms will help to reveal traces of life on Earth and beyond. Among contemporary environments, iron-depositing hot springs (IDHS) may represent one of the most appropriate natural models [1] for insights into ancient life since organisms may have originated on Earth and probably Mars in association with hydrothermal activity [2,3]. IDHS also seem to be appropriate models for studying certain biogeochemical processes that could have taken place in the late Archean and,-or early Paleoproterozoic eras [4, 5]. It has been suggested that inorganic polyphosphate (PPi), in chains of tens to hundreds of phosphate residues linked by high-energy bonds, is environmentally ubiquitous and abundant [6]. Cyanobacteria (CB) react to increased heavy metal concentrations and UV by enhanced generation of PPi bodies (PPB) [7], which are believed to be signatures of life [8]. However, the role of PPi in oxygenic prokaryotes for the suppression of oxidative stress induced by high Fe is poorly studied. Here we present preliminary results of a new mechanism of Fe mineralization in oxygenic prokaryotes, the effect of Fe on the generation of PPi bodies in CB, as well as preliminary analysis of the diversity and phylogeny of proteins involved in the prevention of oxidative stress in phototrophs inhabiting IDHS

Factor structure and construct validity of the Adult Social Care Outcomes Toolkit for Carers (ASCOT-Carer)

Background: The ASCOT-Carer is a self-report instrument designed to measure social care-related quality of life (SCRQoL). This article presents the psychometric testing and validation of the ASCOT-Carer four response-level interview (INT4) in a sample of unpaid carers of adults who receive publicly-funded social care services in England. Methods: Unpaid carers were identified through a survey of users of publicly-funded social care services in England. 387 carers completed a face-to-face or telephone interview. Data on variables hypothesised to be related to SCRQoL (for example, characteristics of the carer, cared-for person and care situation) and measures of carer experience, strain, health-related quality of life and overall QoL were collected. Relationships between these variables and overall SCRQoL score were evaluated through correlation, ANOVA and regression analysis to test the construct validity of the scale. Internal reliability was assessed using Cronbach’s alpha and feasibility by the number of missing responses. Results: The construct validity was supported by statistically significant relationships between SCRQoL and scores on instruments of related constructs, as well as with characteristics of the carer and care recipient in univariate and multivariate analyses. A Cronbach’s alpha of 0.87 (7 items) indicates that the internal reliability of the instrument is satisfactory and a low number of missing responses (<1%) indicates a high level of acceptance. Conclusions: The results provide evidence to support the construct validity, factor structure, internal reliability and feasibility of the ASCOT-Carer INT4 as an instrument for measuring social care-related quality of life of unpaid carers who care for adults with a variety of long-term conditions, disability or problems related to old age

Dutch translation and cross-cultural validation of the Adult Social Care Outcomes Toolkit (ASCOT)

Background: The Adult Social Care Outcomes Toolkit was developed to measure outcomes of social care in England. In this study, we translated the four level self-completion version (SCT-4) of the ASCOT for use in the Netherlands and performed a cross-cultural validation. Methods: The ASCOT SCT-4 was translated into Dutch following international guidelines, including two forward and back translations. The resulting version was pilot tested among frail older adults using think-aloud interviews. Furthermore, using a subsample of the Dutch ACT-study, we investigated test-retest reliability and construct validity and compared response distributions with data from a comparable English study. Results: The pilot tests showed that translated items were in general understood as intended, that most items were reliable, and that the response distributions of the Dutch translation and associations with other measures were comparable to the original English version. Based on the results of the pilot tests, some small modifications and a revision of the Dignity items were proposed for the final translation, which were approved by the ASCOT development team. The complete original English version and the final Dutch translation can be obtained after registration on the ASCOT website (http://www.pssru.ac.uk/ascot). Conclusions: This study provides preliminary evidence that the Dutch translation of the ASCOT is valid, reliable and comparable to the original English version. We recommend further research to confirm the validity of the modified Dutch ASCOT translation

Incremental benefit in correlation with histology of native T1 mapping, partition coefficient and extracellular volume fraction in patients with aortic stenosis

Background: We investigated the histological correlation of native T1 maps, partition coefficient and extracellular volume fraction (ECV) using an 11 heart beat (11 HB) MOLLI for identification of overall burden of fibrosis. Methods: Ten patients (8 male, age 73 ± 7 years; all in sinus rhythm, 2 with ventricular ectopy) with severe aortic stenosis (3 with coexisting coronary artery disease) scheduled for surgical aortic valve replacement underwent CMR on a 1.5T scanner (MAGNETOM Avanto, Siemens Healthcare, Erlangen). The 11HB MOLLI sequence (Siemens investigational prototype WIP 448B) was acquired before and 15 minutes post 0.1 mmol/kg gadolinium administration. Incorporating hematocrit results from the same day. This allowed native T1 maps, partition coefficient and ECV calculation. Images were obtained twice at end diastole at basal, and twice at mid left ventricular level. The average of all measurements was used to calculate ECV using the standard formula Partition Coefficient= [(1/T1myocardium post contrast-1/T1 myocardium native)]/[(1/T1 blood post contrast-1/T1 blood native)] with x(1-HCt) for ECV. Similar regions of interest were drawn in the septum at both levels for T1 values. Intraoperatively, trucut biopsies were taken from the left ventricular apical anterior/ lateral wall through the epicardium to allow histological characterization of the full myocardial wall, and fixed in warm buffered formalin. Histological analysis of formalin-fixed paraffin-embedded, transmural myocardial biopsies of the left ventricle was performed on hematoxylin/eosin and Picrosirius red-stained 3-micron-thick sections by a blinded experienced cardiac pathologist. Images were analysed using a purpose-built software (Nikon NIS elements BR) on a NIKON Eclipse light projection microscope to determine the extent of overall and reactive interstitial fibrosis, which was expressed as collagen volume fraction (%) per square millimetre. Results: Native T1 mapping, partition coefficient and ECV all correlated with histologically measured fibrosis. However, native T1 mapping showed the least accuracy (panel A, R2 = 0.42) and ECV showed the highest accuracy (panel B, R2 = 0.83). Partition coefficient was more accurate than native T1 mapping but only very marginally less so than ECV (panel C, R2 = 0.80). Conclusions: These results suggest that native T1 mapping is less accurate than partition coefficient and ECV for overall fibrosis. Therefore, post gadolinium images to enable calculation of partition coefficient and ECV should be routinely obtained to increase accuracy